Results 1 to 10 of about 641 (184)
An Improved Reduced-Dimension Robust Capon Beamforming Method Using Krylov Subspace Techniques [PDF]
SensorsA reduced-dimension robust Capon beamforming method using Krylov subspace techniques (RDRCB) is a diagonal loading algorithm with low complexity, fast convergence and strong anti-interference ability.
Xiaolin Wang, Xihai Jiang, Yaowu Chen
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Flexible Krylov Methods for Edge Enhancement in Imaging [PDF]
Journal of Imaging, 2021 Many successful variational regularization methods employed to solve linear inverse problems in imaging applications (such as image deblurring, image inpainting, and computed tomography) aim at enhancing edges in the solution, and often involve non ...
Silvia Gazzola +2 more
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Kaczmarz method for saddle point systems [PDF]
E3S Web of Conferences, 2021 The Kaczmarz method is presented for solving saddle point systems. The convergence is analyzed. Numerical examples, compared with classical Krylov subspace methods, SOR-like method (2001) and recent modified SOR-like method (2014), show that the Kaczmarz
Wang Jinmei, Yin Lizi, Wang Ke
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Preconditioners for Krylov subspace methods: An overview [PDF]
GAMM-Mitteilungen, 2020 AbstractWhen simulating a mechanism from science or engineering, or an industrial process, one is frequently required to construct a mathematical model, and then resolve this model numerically. If accurate numerical solutions are necessary or desirable, this can involve solving large‐scale systems of equations.
Pearson, John W., Pestana, Jennifer
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The Hamiltonian extended Krylov subspace method
The Electronic Journal of Linear Algebra, 2022 An algorithm for constructing a $J$-orthogonal basis of the extended Krylov subspace$\mathcal{K}_{r,s}=\operatorname{range}\{u,Hu, H^2u,$ $ \ldots, $ $H^{2r-1}u, H^{-1}u, H^{-2}u, \ldots, H^{-2s}u\},$where $H \in \mathbb{R}^{2n \times 2n}$ is a large (and sparse) Hamiltonian matrix is derived (for $r = s+1$ or $r=s$).
Peter Benner +2 more
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A dual reduction strategy for reduce-order modeling of periodic control system
Results in Control and Optimization, 2021 Model order reduction (MOR) of periodic systems using the Krylov subspace methods received lots of interest in last few decades. In this paper, a structured Krylov subspace based model reduction for linear discrete-time periodic (LDTP) control system has
Mohammad-Sahadet Hossain +2 more
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Krylov Subspace Methods in Dynamical Sampling [PDF]
Sampling Theory in Signal and Image Processing, 2016 Let $B$ be an unknown linear evolution process on $\mathbb C^d\simeq l^2(\mathbb Z_d)$ driving an unknown initial state $x$ and producing the states $\{B^\ell x, \ell = 0,1,\ldots\}$ at different time levels. The problem under consideration in this paper is to find as much information as possible about $B$ and $x$ from the measurements $Y=\{x(i)$, $Bx ...
Akram Aldroubi, Ilya A. Krishtal
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Heat Conduction with Krylov Subspace Method Using FEniCSx
Energies, 2022 The study of heat transfer deals with the determination of the rate of heat energy transfer from one system to another driven by a temperature gradient.
Varun Kumar +3 more
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Fractal and Fractional, 2023 Fractional derivatives and regime-switching models are widely used in various fields of finance because they can describe the nonlocal properties of the solutions and the changes in the market status, respectively.
Xu Chen +3 more
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Pipelined, Flexible Krylov Subspace Methods [PDF]
SIAM Journal on Scientific Computing, 2016 We present variants of the Conjugate Gradient (CG), Conjugate Residual (CR), and Generalized Minimal Residual (GMRES) methods which are both pipelined and flexible. These allow computation of inner products and norms to be overlapped with operator and nonlinear or nondeterministic preconditioner application.The methods are hence aimed at hiding network
Patrick Sanan +2 more
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